How irrelevant inputs affect MLP pattern based learning

We analyze the effect of irrelevant inputs on pattern based learning dynamics of multilayer perceptrons (MLPs). We propose a model for the evolution of weights linking these irrelevant inputs to hidden network nodes. The model is analyzed for a restricted case and the results are illustrated and discussed.